The Hodrick-Prescott filter: a special case of penalized spline smoothing

DOI10.1214/10-EJS570zbMath1329.62200OpenAlexW2103360891MaRDI QIDQ1952084

Yanyan Li

Publication date: 27 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1284557751

zbMATH Keywords

saddlepoint approximationsemiparametric modeleconometric smoothinggross national productparametric bootstrap confidence interval

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric regression and quantile regression (62G08) Parametric tolerance and confidence regions (62F25) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (8)

Parametrizations, weights, and optimal prediction ⋮ TREND EXTRACTION FROM ECONOMIC TIME SERIES WITH MISSING OBSERVATIONS BY GENERALIZED HODRICK–PRESCOTT FILTERS ⋮ Selecting the tuning parameter of the \(\ell_1\) trend filter ⋮ A new method for specifying the tuning parameter of \(\ell_1\) trend filtering ⋮ Exploring US business cycles with bivariate loops using penalized spline regression ⋮ An explicit formula for the smoother weights of the Hodrick-Prescott filter ⋮ Dynamic functional data analysis with non-parametric state space models ⋮ Extensions of saddlepoint-based bootstrap inference

Uses Software

• SemiPar
• ElemStatLearn

Cites Work

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• Exact likelihood ratio tests for penalised splines
• Estimating the Smoothing Parameter in the So-called Hodrick-Prescott Filter

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